Looking into alternatives now that Yahoo finance finally seems like it's gone for good. Came across Alpha Vantage which looks very interesting. The code below is running up until I try to find the delta between the start and end date, but I get the error below:
from alpha_vantage.timeseries import TimeSeries
ts = TimeSeries(key=key, output_format="pandas")
data, meta_data = ts.get_daily("AAPL",outputsize="full")
days = (data.index[-1]- data.index[0]).days
output:
days = (data.index[-1]- data.index[0]).days
TypeError: unsupported operand type(s) for -: 'str' and 'str'
I've also tried:
days = (float(data.index[-1])- float(data.index[0])).days
and
days = (int(data.index[-1])- int(data.index[0])).days
Printed dataframe head as asked below
print(data.head())
Output:
open low close high volume
2000-01-03 104.87 101.69 111.94 112.50 4783900.0
2000-01-04 108.25 101.19 102.50 110.62 4574800.0
2000-01-05 103.75 103.00 104.00 110.56 6949300.0
2000-01-06 106.12 95.00 95.00 107.00 6856900.0
2000-01-07 96.50 95.50 99.50 101.00 4113700.0
No luck with anything, any help would be much appreciated!
It's clear your index is a string. Convert it to datetime like this using df.index.astype:
In [1165]: df.index = df.index.astype(np.datetime64)
Now, what you're doing will work:
In [1166]: (df.index[-1] - df.index[0]).days
Out[1166]: 4